Cloud FinOps SME Enterprise Data Platform (Databricks)
San Jose, CA (Day 1 On-Site)
Long Term
Must Have
~Strong FinOps / cloud cost management experience
~Databricks platform experience
~Ability to manage cloud cost optimization and governance
~Excellent communication skills (role interacts with many departments and directors)
~Candidate must be comfortable discussing financial topics and communicating with multiple stakeholders.
~Technical engineering background
~Experience optimizing Power BI
~Ability to create backlog, epics, and stories for improvement initiatives
Qualifications
6 10 years of experience in cloud cost management, FinOps, platform operations, or technical program management
Strong understanding of public cloud services and pricing models (AWS and/or Azure)
Experience working with data platforms such as Databricks, Apache Spark, or large-scale analytics environments
Experience developing cost analytics, forecasting models, and financial reporting dashboards
Knowledge of cloud cost optimization techniques including rightsizing, autoscaling, workload scheduling, and reserved capacity planning
Experience implementing cost allocation models and tagging strategies for cloud resource tracking
Strong analytical skills with the ability to translate cloud usage data into financial insights and optimization recommendations
Experience collaborating with engineering, finance, and product teams in a cross-functional environment
Experience using data analysis tools such as SQL, Python, or BI platforms for reporting and analytics
Excellent communication skills with the ability to present insights to both technical and non-technical stakeholders
What You Will Do
Monitor, analyze, and optimize cloud spending across Databricks workloads, AWS, and Azure services
Develop and maintain cloud cost visibility dashboards and usage analytics to provide transparency into platform consumption and spending
Partner with Data Engineering, Platform Engineering, and Product teams to implement cost-efficient cloud architecture and workload strategies
Implement and manage cost allocation frameworks (tagging, workspace mapping, business units, products) to track unit economics such as cost per customer, workload, or data pipeline
Develop and maintain cloud consumption forecasting models and support budgeting and financial planning cycles
Establish and promote FinOps governance policies and best practices, including cluster usage guidelines, auto-scaling, instance optimization, and idle resource management
Identify and drive cost optimization initiatives such as cluster right-sizing, workload scheduling, storage lifecycle policies, and reserved capacity planning
Collaborate with Finance teams to support showback and chargeback reporting and improve cost accountability across engineering teams
Analyze Databricks platform utilization patterns and recommend improvements to cluster configurations, job orchestration, and resource usage
Work with cloud service providers on demand planning, reserved instances, savings plans, and capacity reservations
Identify opportunities for automation and process improvement in cloud cost management and reporting
Track and report FinOps KPIs, optimization initiatives, and realized savings
Nice to Have
FinOps Foundation FinOps Certified Practitioner certification
Experience working with Databricks cost optimization and cluster management
Familiarity with cloud cost management tools such as CloudHealth, Cloudability, or native cloud cost management platforms
Experience building cost dashboards using BI tools such as Power BI, Tableau, or Looker
Knowledge of enterprise data platform architecture
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